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Text Extraction from Scrolling News Tickers

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Databases and Information Systems (DB&IS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1243))

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Abstract

While a lot of work exists on text or keyword extraction from videos, not a lot can be found on the exact problem of extracting continuous text from scrolling tickers. In this work a novel Tesseract OCR based pipeline is proposed for location and continuous text extraction from scrolling tickers in videos. The solution worked faster than real time, and achieved a character accuracy of 97.3% on 45 min of manually transcribed 360p videos of popular Latvian news shows.

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Acknowledgements

The authors would like to thank the reviewers for their thought provoking comments.

The research was supported by ERDF project 1.1.1.1/18/A/045 at IMCS, University of Latvia.

Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of Latvia, Raina blvd. 29, Riga, 1459, Latvia

    Ingus Janis Pretkalnins & Arturs Sprogis

  2. LETA, Marijas 2, Riga, 1050, Latvia

    Guntis Barzdins

Authors
  1. Ingus Janis Pretkalnins
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  2. Arturs Sprogis
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  3. Guntis Barzdins
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Corresponding author

Correspondence to Ingus Janis Pretkalnins .

Editor information

Editors and Affiliations

  1. Department of Computer Systems, Tallinn University of Technology, Tallinn, Estonia

    Tarmo Robal

  2. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Hele-Mai Haav

  3. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Jaan Penjam

  4. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Raimundas Matulevičius

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Pretkalnins, I.J., Sprogis, A., Barzdins, G. (2020). Text Extraction from Scrolling News Tickers. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_11

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  • DOI: https://doi.org/10.1007/978-3-030-57672-1_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57671-4

  • Online ISBN: 978-3-030-57672-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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